Efficient coding of side information in a lossless encoder

ABSTRACT

For “Super Audio CD” (SACD) the DSD signals are losslessly coded, using framing, prediction and entropy coding. Besides the efficiently encoded signals, a large number of parameters, i.e. the side-information, has to be stored on the SACD too. The smaller the storage capacity that is required for the side-information, the better the overall coding gain is. Therefore coding techniques are applied to the side-information too so as to compress the amount of data of the side information.

[0001] The invention relates to an apparatus for lossless encoding of adigital information signal, for a lossless encoding method, to anapparatus for decoding and to a record carrier.

[0002] For “Super Audio CD” (SACD) the DSD signals are losslessly coded,using framing, prediction and entropy coding. Besides the efficientlyencoded signals, a large number of parameters, i.e. theside-information, has to be stored on the SACD too. The smaller thestorage capacity that is required for the side-information, the betterthe overall coding gain is. Therefore coding techniques are applied tothe side-information too. A description of the lossless encoding of DSDsignals is given in the publication ‘Improved lossless coding of 1-bitaudio signals’, by F. Bruekers et al, preprint 4563(I-6) presented atthe 103^(rd) convention of the AES, Sep. 26-29, 1997 in New York.

[0003] The invention aims at providing methods that can be used e.g. inSACD to save on the number of bits that have to be used for storing theside-information. In the following description those methods will bepresented.

[0004] These and other aspects of the invention will be furtherexplained hereafter in the figure description, in which

[0005]FIG. 1a shows a circuit diagram of a lossless encoder and FIG. 1bshows a circuit diagram of a corresponding decoder, using linearprediction and arithmetic coding,

[0006]FIG. 2 shows subsequent frames of a multi channel informationsignal,

[0007]FIG. 3 shows the segmentation of time equivalent frames of themulti channel information signal, and

[0008]FIG. 4 shows the contents of a frame of the output signal of theencoding apparatus.

[0009] The process of lossless encoding and decoding, for the example of1-bit oversampled audio signals, will be explained briefly hereafter bymeans of FIG. 1, which shows an embodiment of the encoder apparatus inFIG. 1 a and shows an embodiment of the decoder apparatus in FIG. 1b.

[0010] The lossless coding in the apparatus of FIG. 1a is performed onisolated parts (frames) of the audio signal. A typical length of such aframe is 37632 bits. The two possible bit-values of the input signal F,‘1’ and ‘0’, represent the sample values +1 and −1 respectively. Perframe, the set of coefficients for the prediction filter z⁻¹ .A(z),denoted by 4, is determined in a filter coefficient generator unit 12,by e.g. the autocorrelation method. The sign of the filter outputsignal, Z, determines the value of the predicted bit F_(p), whereas themagnitude of the filter output signal, Z, is an indication for theprobability that the prediction is correct. Upon quantizing the filteroutput signal Z in a quantizer 10, a predicted input signal F_(p) isobtained, which is ex-ored in a combining unit 2, resulting in aresidual signal E. A correct prediction, or F=F_(p), is equivalent toE=0 in the residual signal E. The content of the probability table,p(|.|), is designed per frame such that per possible value of Z, p₀ isthe probability that E=0. For small values of |Z| the probability for acorrect prediction is close to 0.5 and for large values of |Z| theprobability for a correct prediction is close to 1.0. Clearly theprobability for an incorrect prediction, F≠F_(p) or E=1, is p₁=1p₀.

[0011] The probability tables for the frames (or segments, to bedescribed later) are determined by the unit 13. Using this probabilitytable, supplied by the unit 13 to the unit 8, the unit 8 generates aprobability value P₀ in response to its input signal, which is thesignal Z.

[0012] The arithmetic encoder (AC Enc.) in the apparatus of FIG. 1a,denoted by 6, codes the sequence of bits of E such that the code (D)requires less bits. For this, the arithmetic coder uses the probabilitythat bit n of signal E, E[n], has a particular value. The number of bitsto code the bit E[n]=0 is:

d _(n)=2 log(p ₀)+ε(bits)  (Eq. 1)

[0013] which is practically not more than 1 bit, since p₀≧½. The numberof bits to code the bit E[n]=1 is:

d _(n)=2 log(p ₁)+ε=−² log(1−p ₀)+ε(bits)  (Eq. 2)

[0014] which is not less than 1 bit. The ε in both equations representsthe non-optimal behavior of the arithmetic coder, but can be neglectedin practice.

[0015] A correct prediction (E[n]=0) results in less than 1 bit and anincorrect prediction (E[n]=1) results in more than 1 bit in the code(D). The probability table is designed such that on the average for thecomplete frame, the number of bits for code D is minimal.

[0016] Besides code D, also the coefficients of the prediction filter 4,generated by the coefficient generator unit 12, and the content of theprobability table, generated by the probability table determining unit13, have to be transmitted from encoder to decoder. To that purpose, theencoder apparatus comprises a multiplexer unit 14, which receives theoutput signal of the coder 6, as well as side information from thegenerator units 12 and 13. This side information comprises theprediction filter coefficients and the probability table. Themultiplexer unit 14 supplies the serial datastream of information to atransmission medium, such as a record carrier.

[0017] In the decoder apparatus of FIG. 1b, exactly the inverse of theencoder process is implemented thus creating a lossless coding system.The demultiplexer unit 20 receives the serial datastream comprising thedata D and the side information. It retrieves the data D therefrom andsupplies the data D to an arithmetic decoder 22. The arithmetic decoder(AC Dec.) is provided with the identical probabilities as the arithmeticencoder was, to retrieve the correct values of signal E. Therefore thedemultiplexer unit retrieves the same prediction filter coefficients andprobability table as used the encoder from the serial datastreamreceived and supplies the prediction filter coefficients to theprediction filter 24 and the probability table to the probability valuegenerator unit 26.

[0018] The circuit constructions shown in FIG. 1 are meant forencoding/decoding a single serial datastream of information.Encoding/decoding a multi channel information signal, such as a multichannel digital audio signal, requires the processing described abovewith reference to FIG. 1 to be carried out in time multiplex by thecircuits of FIG. 1, or can be carried out in parallel by a plurality ofsuch circuits. Another solution can be found in international patentapplication IB 99/00313, which corresponds to U.S. Ser. No. 09/268,252(PHN 16.805).

[0019] It should be noted here that in accordance with the invention,the encoding apparatus may be devoid of the quantizer Q and thecombining unit 2. Reference is made to earlier patent publicationsdiscussing this.

[0020] In SACD the 1-bit audio channels are chopped into frames ofconstant length and per frame the optimal strategy for coding will beused. Frames can be decoded independently from neighbouring frames.Therefore we can discuss the data structure within a single frame.

[0021]FIG. 2 shows time equivalent frames B of two channel signals, suchas the left and right hand signal component of a digital stereo audiosignal, indicated by . . . , B(l,m-1), B(l,m), B(l,m+1), . . . for theleft hand signal component and by . . . , B(r,m−1), B(r,m), B(r,m+1), .. . for the right hand signal component. The frames can be segmented, aswill be explained hereafter. If not segmented, the frames will beencoded in their entirety, with one set of filter coefficients and oneprobability table for the complete frame. If segmented, each segment ina frame can have its own set of filter coefficients and probabilitytable. Furthermore, the segmentation in a frame for the filtercoefficients need not be the same as for the probability tables. As anexample, FIG. 3 shows the two time equivalent frames B(l,m) and B(r,m)of the two channel signals being segmented. The frame B(l,m) has beensegmented into three segments fs(1,1), fs(1,2) and fs(1,3) in order tocarry out three different prediction filterings in the frame. It shouldhowever be noted that the filterings in two segments, such as thesegments fs(1,1) and fs(1,3) can be the same. The frame B(l,m) hasfurther been segmented into two segments ps(1,1) and ps(1,2) in order tohave two different probability tables for those segments.

[0022] The frame B(r,m) has been segmented into three segments fs(r,1),fs(r,2) and fs(r,3) in order to carry out three different predictionfilterings in the frame. It should however again be noted that thefilterings in two segments, such as the segments fs(r,1) and fs(r,3) canbe the same. The frame B(r,m) has further been segmented into foursegments ps(r,1), ps(r,2), ps(r,3) and ps(r,4) in order to have fourdifferent probability tables for those segments. Again, it should benoted that some of the segments can have the same probability table.

[0023] The decision to have the same probability table for differentsegments can be taken on beforehand by a user of the apparatus, afterhaving carried out a signal analysis on the signals in the segments. Orthe apparatus may be capable of carrying out this signal analysis anddecide in response thereto. In some situations, a signal analysiscarried out on two segments may result in probability tables that differonly slightly. In such situation, it can be decided to have one and thesame probability table for both segments. This one probability tablecould be equal to one of the two probability tables established for thetwo segments, or could be an averaged version of both tables. Anequivalent reasoning is valid for the sets of filter coefficients in thevarious segments.

[0024] To summarize: in order to encode a small portion of audio in anaudio channel signal, the coding algorithm in SACD requires both aprediction filter (the filter) and a probability table (the table). Forimproving the coding gain it can be efficient to use different filtersin different channels. But also within the same channel is can bebeneficial to use different filters. That is why the concept ofsegmentation is introduced. A channel is partitioned into segments andin a segment a particular filter is used. Several segments, also fromother channels, may use the same or a different filter. Besides storageof the filters that are used, also information about the segments(segmentation) and information about what filter is used in what segment(mapping) have to be stored.

[0025] For the tables, the same idea is applicable, however thesegmentation and mapping may be different from the segmentation andmapping for the filters. In case of equal segmentation for both filterand table this is indicated. The same idea is used for the mapping. Ifthe segmentation for the filters is equal for all channels this isindicate too. The same idea is used for the mapping.

[0026] First, a description will be given of the contents of a frame ofa transmission signal comprising the encoded channel signals and thecorresponding side information. FIG. 4 shows a schematic drawing of theframe. Apart from synchronization information (not shown), the framecomprises two words w₁ and w₂, followed by segmentation information onthe prediction filters. Next a word w₃ is present followed bysegmentation information on the probability tables. Next follow twowords w₄ and w₅, followed by mapping information on the predictionfilters. Next, follows a word w₆, followed by mapping information on theprobability tables. Next follow the filter coefficients and theprobability tables, as supplied by the generator units 12 and 13,respectively. The frame ends with the data D, supplied by the arithmeticencoder 6.

[0027] The word w₁ is in this example one bit long and can have thevalue ‘0’ or ‘1’, and indicates whether the segment information for thefilter coefficients and the probability tables are the same (‘1’), ornot (‘0’). The word w₄ is in this example one bit long and can have thevalue ‘0’ or ‘1’, and indicates whether the mapping information for thefilter coefficients and the probability tables are the same (‘1’), ornot (‘0’). The word w₂, again one bit long, can have the value ‘0’ or‘1’, and indicates whether the channel signals have the samesegmentation information for the prediction filter coefficients (‘1’),or not (‘0’). The word w₃ (one bit long) can have the value ‘0’ or ‘1’,and indicates whether the channel signals have the same segmentationinformation for the probability tables (‘1’), or not (‘0’). The word w₅can have the value ‘0’ or ‘1’, and indicates whether the channel signalshave the same mapping information for the prediction filter coefficients(‘1’), or not (‘0’). The word w₆ can have the channel signals have thesame mapping information e total number of segments S in a frame will betal number of segments in a frame in a particular s applied. It isimportant that the code is short for ments in a channel S≧1, S=0 needsnot to be d. TABLE 1 S code(S) 1 1 2 01 3 001 4 0001 s 0^((s−1))1

[0028] as delimiter. It is clear that in general the role of sic idea ofthe delimiter is that a certain sequence by a “1”. An alternative ise.g. to “inverse” the delimiter. In this way long constant sequences arethat start with an “1” is (not used in SACD): S code(S) 1 0 2 11 3 100 41011 5 10100 6 101011

[0029] Second, the representation of the segment sizes will bedescribed. The length of a segment will be expressed in number of bytesof the channel signal. The B bytes in a frame of a channel signal arepartitioned into S segments. For the first S−1 segments the number ofbytes of each segment has to be specified. For the S^(th) segment thenumber of bytes is specified implicitly, it is the remaining number ofbytes in the channel. The number of bytes in segment i, equals

[0030] B_(i) so the number of bytes in the last segment is:$B_{s - 1} = {B - {\sum\limits_{i = 0}^{s - 2}B_{i}}}$

[0031] Since the number of bytes in the first S−1 segments are multiplesof R the resolution R≧1, we define:

[0032] B_(i)=b_(i)R and consequently:$B_{s - 1} = {B - {\sum\limits_{i = 0}^{s - 2}{b_{i}R}}}$

[0033] The S−1 values of b_(i) are stored and R is stored in a channelonly if S>1 and when it is not stored already for another channel.

[0034] The number of bits required to store b_(i) depends on itspossible values.

[0035] 0≦b_(i)≦b_(i,max) with e.g.$b_{i,\max} = {\left\lfloor \frac{B}{R} \right\rfloor - {\sum\limits_{j = 0}^{i - 1}b_{j}}}$

[0036] so the required number of bits to store b_(i) is:

[0037] #bits(b_(i))=└²log(b_(i,max))┘+1

[0038] This has as advantage that the required number of bits for thesegment length may decrease for segments at the end of the frame. Ifrestrictions are imposed on e.g. minimal length of a segment thecalculation of the number of bits may be adapted accordingly. The numberof bits to store the resolution R is: #bits(R)

[0039] Third, the representation of the segmentation information in theserial datastream will be described. Use will be made of therepresentations given above under table 1. This will be illustrated bysome examples.

[0040] In order to distinguish between filters and probability tables,the subscripts f and t are used. To distinguish between segments indifferent channels the double argument is used: (channel number, segmentnumber).

[0041] Next follows a first example. For a 2-channel case, we havedifferent segmentations for filters and probability tables, and thesegmentation is different for both channels. The following table showsthe parameters in the stream. TABLE 2 Value #bits comment (w₁ =) 0 1segmentation information for the filters is different from thesegmentation for the probability tables filter segmentation (w₂ =) 0 1channels have own filter segmentation information filter segmentation inchannel 0 (y₁ =) 0 1 first bit of code(S_(f)(0)) indicating thatS_(f)(0) ≧ 2 R_(f) #bits(R_(f)) resolution for filters b_(f)(0,0)#bits(b_(f)(0,0)) first segment in channel 0 has length R_(f) b_(f)(0,0)bytes (y₂ =) 1 1 last bit of code(S_(f)(0)) indicating that S_(f)(0) = 2filter segmentation in channel 1 (y₁ =) 0 1 first bit of code(S_(f)(1))indicating that S_(f)(1) ≧ 2 b_(f)(1,0) #bits(b_(f)(1,0)) first segmentin channel 1 has length R_(f) b_(f)(1,0) bytes (y₂ =) 0 1 second bit ofcode(S_(f)(1)) indicating that S_(f)(1) ≧ 3 b_(f)(1,1) #bits(b_(f)(1,1))second segment in channel 1 has length R_(f) b_(f)(1,1) bytes (y₃ =) 1 1last bit of code(S_(f)(1)) indicating that S_(f)(1) = 3 probabilitytable segmentation (w₃ =) 0 1 channels have own table segmentationspecification probability table segmentation in channel 0 (y₁ =) 1 1last bit of code(S_(t)(0)) indicating that S_(t)(0) = 1 probabilitytable segmentation in channel 1 (y₁ =) 0 1 first bit of code(S_(t)(1))indicating that S_(t)(1) ≧ 2 R_(t) #bits(R_(t)) resolution for tablesb_(t)(1,0) #bits(b_(t)(1,0)) first segment in channel 1 has length R_(t)b_(t)(1,0) bytes (y₂ =) 0 1 second bit of code(S_(t)(1)) indicating thatS_(t)(1) ≧ 3 b_(t)(1,1) #bits(b_(t)(1,1)) second segment in channel 1has length R_(t) b_(t)(1,1) bytes (y₃ =) 1 1 last bit of code(S_(t)(1))indicating that S_(t)(1) = 3

[0042] In the above table 2, the first combination (y₁,y₂) equal to(0,1) is the codeword code(S) in table 1 above, and indicates that inthe channel signal numbered 0 the frame is divided into two segments forthe purpose of prediction filtering. Further, the combination (y₁,y₂,y₃)equal to. (0,0,1) is the codeword code(S) in table 1 above, andindicates that in the channel signal numbered 1 the frame is dividedinto three segments for the purpose of prediction filtering. Next, wefind a combination (ye) equal to (1), which is the first codeword intable 1, indicating that the channel signal numbered 0, the frame is notdivided for the probability table. Finally, we find a combination(y₁,y₂,y₃) equal to (0,0,1), which indicates that the frame of thesecond channel signal is divided into three segments, each with acorresponding probability table.

[0043] Next, follows another example for a 5-channel case. It is assumedthat for this 5-channel case, we have equal segmentation for filters andtables, and the segmentation is equal for all channels. Value #bitscomment (w₁ =) 1 1 the segmentation information for the predictionfilters and probability tables is the same filter segmentation (w₂ =) 11 channels have equal filter segmentation informa- tion filtersegmentation in channel 0 (y_(t) =) 0 1 first bit of code(S_(f)0))indicating that S_(f)(0) ≧ 2 R_(f) #bits(R_(f)) resolution for filtersb_(f)(0,0) #bits(b_(f)0,0)) first segment in channel 0 has length R_(f)b_(f)(0,0) bytes (y₂ =) 0 1 second bit of code(S_(f)(0)) indicating thatS_(f)(0) ≧ 3 b_(f)(0,1) #bits(b_(f)0,1)) second segment in channel 0 haslength R_(f) b_(f)(0,1) bytes (y₃ =) 1 1 last bit of code(S_(f)(0))indicating that S_(f)(0) = 3 filter segmentation in channel c b_(f)(c,0)= b_(f)(0,0) and b_(f)(c,1) = b_(f)(0,1) for 1 ≦ c < 5 probability tablesegmentation in channel c b_(t)(c,0) = b_(f)(0,0) and b_(t)(c,1) =b_(f)(0,1) for 0 ≦ c < 5

[0044] Remark: The single bits of code(S) interleaved in de segmentationinformation can be interpreted as “another segment will be specified” incase of “0” or “no more segments will be specified” in case of “1”.

[0045] Next, mapping will be described.

[0046] For each of the segments, all segments of all channels areconsidered together, it has to be specified which filter or table isused. The segments are ordered; first the segments of channel 0 followedby the segments of channel 1 and so on.

[0047] The filter or table number for segment s, N(s) is defined as:$\left\{ \begin{matrix}{{N(0)} = 0} \\{0 \leq {N(s)} \leq {N_{\max}(s)}}\end{matrix}\quad \right.$

[0048] with N_(max) (s), the maximum allowed number for a given segment,defined as:

[0049] N_(max)(s)=1+max(N(i)) with 0≦i<s

[0050] The required number of bits to store N(s) equals:

[0051] #bits(N(s))=└²log(N_(max)(s))┘+1

[0052] The number of bits that is required to store a filter or tablenumber according to this method depends on the set of numbers thatalready has been assigned.

[0053] If the tables use the same mapping as the filters, which is notalways possible, this is indicated. Also when all channels use the samemapping this is indicated.

[0054] With two examples the idea will be illustrated.

EXAMPLE 3

[0055] Assume that in total we have 7 segments (0 through 6), somesegments use the same filter and some use a unique filter. Furthermoreit is assumed that the tables use the same mapping specification as thefilters. Channel Segment Filter Possible filter number number numbernumbers #bits 0 0 0 — 0 1 1 0 0 or 1 1 1 2 1 0 or 1 1 1 3 2 0, 1 or 2 21 4 3 0, 1, 2 or 3 2 2 5 3 0, 1, 2, 3 or 4 3 3 6 1 0, 1, 2, 3 or 4 3Total #bits 12 

[0056] Segment number 0 uses filter number 0 per definition, so no bitsare needed for this specification. Segment number 1 may use an earlierassigned filter (0) or the next higher not yet assigned filter (1), so 1bit is needed for this specification. Segment number 1 uses filternumber 0 in this example. Segment number 2 may use an earlier assignedfilter (0) or the next higher not yet assigned filter (1), so 1 bit isneeded for this specification. Segment number 2 uses filter number 1 inthis example.

[0057] Segment number 3 may use an earlier assigned filter (0 or 1) orthe next higher not yet assigned filter (2), so 2 bits are needed forthis specification. Segment number 3 uses filter number 2 in thisexample.

[0058] Segment number 4 may use an earlier assigned filter (0, 1 or 2)or the next higher not yet assigned filter (3), so 2 bits are needed forthis specification. Segment number 4 uses filter number 3 in thisexample. Segment number 5 may use an earlier assigned filter (0, 1, 2 or3) or the next higher not yet assigned filter (4), so 3 bits are neededfor this specification. Segment number 5 uses filter number 3 in thisexample.

[0059] Segment number 6 may use an earlier assigned filter (0, 1, 2 or3) or the next higher not yet assigned filter (4), so 3 bits are neededfor this specification. Segment number 6 uses filter number 1 in thisexample.

[0060] In total 12 bits are required to store the mapping. The totalnumber of segments (7 segments in this example) is known at this pointin the stream. Value #bits comment (w₄ =) 1 1 probability tables havesame mapping information as prediction filters prediction filter mapping(w₅ =) 0 1 channels have own filter, segmentation information 0 filternumber for segment 0 is 0 per definition N_(f)(1) #bits(N_(f)(1)) filternumber for segment 1 N_(f)(2) #bits(N_(f)(2)) filter number for segment2 N_(f)(3) #bits(N_(f)(3)) filter number for segment 3 N_(f)(4)#bits(N_(f)(4)) filter number for segment 4 N_(f)(5) #bits(N_(f)(5))filter number for segment 5 N_(f)(6) #bits(N_(f)(6)) filter number forsegment 6 probability table mapping N_(t)(i) = N_(f)(i) for 0 ≦ i < 7

[0061] Another example. Assume that in total we have 6 channels eachwith 1 segment and each segment uses the same prediction filter and thesame probability table. Value #bits comment (w₄ =) 1 1 probabilitytables have same mapping information as prediction filters predictionfilter mapping (w₅ =) 1 1 channels have own filter mapping specification0 filter number for segment 0 is 0 per definition prediction filtermapping for segment i N_(f)(i) = 0 for 1 ≦ i < 6 probability tablemapping for segment i N_(t)(i) = N_(f)(i) for 0 ≦ i < 6

[0062] In total 2 bits are required to store the complete mapping.

[0063] Remark: A reason to give the indication that a followingspecification is also used for other application (e.g. for tables thesame segmentation is used as for the filters) is that this simplifiesthe decoder.

[0064] Whilst the invention has been described with reference topreferred embodiments thereof, it is to be understood that these are notlimitative examples. Thus, various modifications may become apparent tothose skilled in the art without departing from the scope of theinvention as defined by the claims. As an example, the invention couldalso have been incorporated in an embodiment in which time equivalentsignal blocks are encoded, without making use of segmentation. In suchembodiment, the serial datastream obtained, like the datastream of FIG.4, will be devoid of the segment information described there for thefilters and the probability tables, as well as some of the indicatorwords, such as the indicator words w₁, w₂ and w₃. Further, the inventionlies in each and every novel feature and combination of features.

1. Apparatus for encoding of a digital information signal, such as ann-channel digital audio signal, where n is an integer larger than 1,comprising input means for receiving the digital information signal,encoding means for encoding the digital information signal so as toobtain an encoded digital information signal, the encoding means beingadapted to encode each of said channel signals of the n-channel digitalaudio signal so as to obtain an encoded channel signal for each of saidchannel signals in response to probability values for each of saidchannel signals, prediction filter means for carrying out a predictionfiltering-on each of said channel signals of the n-channel digital audiosignal in response to a set of prediction filter coefficients for eachof said channel signal so as to obtain a prediction filtered channelsignal from each of said channel signals, prediction filter coefficientdetermining means for generating a set of prediction filter coefficientsfor each of said channel signals, probability value determining meansfor generating probability values for each of said channel signals inresponse to a probability table for each of said channel signals and thecorresponding prediction filtered channel signal for each of saidchannel signals, probability table determining means for generating theprobability tables for each of said channel signals, converting meansfor generating first mapping information and a plurality of m sets ofprediction filter coefficients, where m is an integer for which holds1≦m≦n, said first mapping information and m sets of prediction filtercoefficients being representative of said n sets of prediction filtercoefficients for said n channels, and for generating second mappinginformation and a plurality of p probability tables, where p is aninteger for which holds 1≦p≦n, said second mapping information and pprobability tables being representative of said n probability tables forsaid n channels, combining means for combining said compressed digitalinformation signal, said first and second mapping information signals,said plurality of m sets of prediction filter coefficients and saidplurality of p probability tables into a composite information signal,output means for outputting said composite information signal. 2.Apparatus for encoding of a digital information signal, such as ann-channel digital audio signal, where n is an integer larger than 1,comprising input means for receiving the digital information signal,encoding means for encoding the digital information signal so as toobtain an encoded digital information signal, the encoding means beingadapted to encode time equivalent signal blocks of each of said channelsignals of the n-channel digital audio signal by dividing the timeequivalent signal blocks into M segments, and encoding the signalportions of the channel signals in all M segments in said timeequivalent signal blocks, so as to obtain an encoded signal portion foreach of said signal portions in said M segments in response toprobability values for each of said signal portions, where$M = {\sum\limits_{i = 0}^{i = {n - 1}}{sp}_{i}}$

and sp_(i) is the number of segments in the time equivalent signal blockof the i-th channel signal, probability value determining means forgenerating probability values for each of said M signal portions inresponse to a probability table for each of said M signal portions,probability table determining means for generating the probabilitytables for each of said M signal portions, converting means forconverting the information about the length and locations of the Msegments in the n channel signals into first segment information, andfor generating first mapping information and a plurality of mprobability tables, where m is an integer for which holds 1≦m≦M, saidfirst mapping information and said m probability tables beingrepresentative for said M probability tables, combining means forcombining the portion of the encoded digital information signalcomprised in said time equivalent signal blocks, said first segmentinformation, said first mapping information signal and said plurality ofm probability tables into a composite information signal, output meansfor outputting said composite information signal.
 3. Apparatus asclaimed in claim 2, further comprising prediction filter means forcarrying out a prediction filtering on the digital information signal soas to obtain a prediction filtered digital information signal, theprediction filter means being adapted to prediction filter timeequivalent signal blocks of each of said channel signals of then-channel digital audio signal by dividing the time equivalent signalblocks into segments, and prediction filtering the signal portions ofthe channel signals in all P segments in said time equivalent signalblocks, so as to obtain a prediction filtered signal portion for each ofsaid P signal portions in response to a set of prediction filtercoefficients for each of said signal portions, where$P = {\sum\limits_{i = 0}^{i = {n - 1}}{sf}_{i}}$

and sf_(i) is the number of segments in the time equivalent signal blockof the i-th channel signal, prediction filter coefficient determiningmeans for generating a set of prediction filter coefficients for each ofsaid P signal portions, the converting means further being adapted toconvert the information about the length and locations of the P segmentsin the n channel signals into second segment information, and forgenerating second mapping information and a plurality of p sets ofprediction filter coefficients, where p is an integer for which holds1≦p≦P, said second mapping information and said p sets of predictionfilter coefficients being representative of said P sets of predictionfilter coefficients, the combining means further being adapted tocombine said second segment information, said second mapping informationsignal and said plurality of p sets of prediction filter coefficientsinto said composite information signal.
 4. Apparatus as claimed in claim3, wherein the conversion means is adapted to generate a first indicatorword (w₁) of a first value, indicating that the segmentation of the timeequivalent signal blocks for the probability tables is different fromthe segmentation of the time equivalent signal blocks for the sets ofprediction filter coefficients and of a second value indicating that thesegmentation of the time equivalent signal blocks for the probabilitytables is the same as for the prediction filter coefficients, and forsupplying only one of the first or the second segment information in thelatter case, the combining means being adapted to combine the firstindicator word and the only one of the first segment information or thesecond segment information into said composite information signal, inthe case that the first indicator word has the second value. 5.Apparatus as claimed in claim 4, wherein the conversion means is adaptedto generate said only one of the first or second segment information inthe case that the first indicator word has the second value. 6.Apparatus as claimed in claim 3, wherein the conversion means is adaptedto generate a second indicator word (w₂) of a third value indicatingthat the time equivalent signal blocks all have the same segmentationfor the sets of prediction filter coefficients and is adapted togenerate a second indicator word of a fourth value indicating that thetime equivalent signal blocks have each a different segmentation for thesets of prediction filter coefficients, that the converting means isadapted to generate second segment information for only one timeequivalent signal block in the case that the second indicator word hasthe third value and is adapted to generate second segment informationfor each of the time equivalent signal blocks in the case that thesecond indicator word has the fourth value, and that the combining meansis further adapted to combine the second indicator word into saidcomposite information signal.
 7. Apparatus as claimed in claim 2,wherein the conversion means is adapted to generate a third indicatorword (w₃) of a fifth value indicating that the time equivalent signalblocks all have the same segmentation for the probability tables and isadapted to generate a third indicator word of a sixth value indicatingthat the time equivalent signal blocks have each a differentsegmentation for the probability tables, that the converting means isadapted to generate first segment information for only one timeequivalent signal block in the case that the third indicator word hasthe fifth value and is adapted to generate first segment information foreach of the time equivalent signal blocks in the case that the thirdindicator word has the sixth value, and that the combining means isfurther adapted to combine the third indicator word into said compositeinformation signal.
 8. Apparatus as claimed in claim 3, wherein theconversion means is adapted to generate a fourth indicator word (w₄) ofa seventh value, indicating that the mapping information for theprobability tables is different from the mapping information for theprediction filter coefficients and of an eighth value indicating thatthe mapping information for the probability tables is the same as forthe prediction filter coefficients, and for supplying the first or thesecond mapping information only in the latter case, the combining meansbeing adapted to combine the fourth indicator word and the first mappinginformation or the second mapping information only into said compositeinformation signal, in the case that the fourth indicator word has theeighth value.
 9. Apparatus as claimed in claim 3, wherein the conversionmeans is adapted to generate a fifth indicator word (w₅) of a ninthvalue indicating that the time equivalent signal blocks all have thesame mapping information for the sets of prediction filter coefficientsand is adapted to generate a fifth indicator word of a tenth valueindicating that the time equivalent signal blocks have each a differentmapping information for the sets of prediction filter coefficients, thatthe converting means is adapted to generate second mapping informationfor only one time equivalent signal block in the case that the fifthindicator word has the ninth value and is adapted to generate secondmapping information for each of the time equivalent signal blocks in thecase that the fifth indicator word has the tenth value, and that thecombining means is further adapted to combine the fifth indicator wordinto said composite information signal.
 10. Apparatus as claimed inclaim 2 or 3, the conversion means being further adapted to convertinginformation concerning the number of segments in a time equivalentsignal block of a channel signal into a number code, the combining meansbeing further adapted to combine the number code into said compositeinformation signal.
 11. Apparatus as claimed in claim 10, wherein saidnumber code satisfies the following table: S code(S) 1 1 2 01 3 001 40001 s 0^((s−1))1

where S is the number of segments in a time equivalent signal block of achannel signal.
 12. Apparatus as claimed in claim 3, wherein the firstset of prediction filter coefficients is allocated to the first of saidP segments, said second mapping information being devoid of mappinginformation for mapping said first set of prediction filter coefficientsto said first segment of said P segments, (a) the first bit in saidsecond mapping information indicating whether the set of predictionfilter coefficients for the second segment is the first set ofprediction filter coefficients or a second set of prediction filtercoefficients, (b1) if the first set of prediction filter coefficients isalso the set of filter coefficients for the second segment, then thesecond bit in said second mapping information indicating whether the setof prediction filter coefficients for the third segment is the first setof prediction filter coefficients or the second set of prediction filtercoefficients, (b2) if the second set of prediction filter coefficientsis the set of filter coefficients for the second segment, then the nexttwo bits in the second mapping information indicating whether the set ofprediction filter coefficients for the third segment is the first, thesecond or the third set of prediction filter coefficients, (c1) if thefirst set of prediction filter coefficients is the set of filtercoefficients for the second and third segment, then the third bit ofsaid second mapping information indicates whether the set of predictionfilter coefficients for the fourth segment is the first or the secondset of prediction filter coefficients, (c2) if the first set ofprediction filter coefficients is the set of filter coefficients for thesecond segment and the second set of prediction filter coefficients isthe set of filter coefficients for the third segment, then the third andfourth bit in said second mapping information indicating whether the setof prediction filter coefficients for the fourth segment is the first,the second or the third set of prediction filter coefficients, (c3) ifthe second set of prediction filter coefficients is the set of filtercoefficients for the second segment, and the first or the second set offilter coefficients is the set of filter coefficients for the thirdsegment, then the fourth and fifth bit in the second mapping informationindicating whether the set of prediction filter coefficients for thefourth segment is the first, second or the third set of predictionfilter coefficients, (c4) if the second set of prediction filtercoefficients is the set of filter coefficients for the second segment,and the third set of filter coefficients is the set of prediction filtercoefficients for the third segment, then the fourth and fifth bit in thesecond mapping information indicating whether the set of predictionfilter coefficients for the fourth segment is the first, second, thirdor the fourth set of filter coefficients.
 13. Apparatus as claimed inclaim 2, wherein the first probability table is allocated to the firstof said M segments, said first mapping information being devoid ofmapping information for mapping said first probability table to saidfirst segment of said M segments, (a) the first bit in said firstmapping information indicating whether the probability table for thesecond segment is the first probability table or a second probabilitytable, (b1) if the first probability table is also the probability tablefor the second segment, then the second bit in said first mappinginformation indicating whether the probability table for the thirdsegment is the first probability table or the second probability table,(b2) if the second probability table is the probability table for thesecond segment, then the next two bits in the first mapping informationindicating whether the probability table for the third segment is thefirst, the second or the third probability table, (c1) if the firstprobability table is the probability table for the second and thirdsegment, then the third bit of said first mapping information indicateswhether the probability table for the fourth segment is the first or thesecond probability table, (c2) if the first probability table is theprobability table for the second segment and the second probabilitytable is the probability table for the third segment, then the third andfourth bit in said first mapping information indicating whether theprobability table for the fourth segment is the first, the second or thethird probability table, (c3) if the second probability table is theprobability table for the second segment, and the first or the secondprobability table is the probability table for the third segment, thenthe fourth and fifth bit in the first mapping information indicatingwhether the probability table for the fourth segment is the first,second or the third probability table, (c4) if the second probabilitytable is the probability table for the second segment, and the thirdprobability table is the probability table for the third segment, thenthe fourth and fifth bit in the first mapping information indicatingwhether the probability table or the fourth segment is the first,second, third or the fourth probability table.
 14. Apparatus as claimedin anyone of the preceding claims, characterized in that said outputmeans comprises writing means for writing the composite informationsignal on a record carrier.
 15. Apparatus as claimed in claim 14,characterized in that said output means further comprises channelencoding and/or error correction encoding means for carrying out achannel encoding step and/or an error correction encoding step on saidcomposite information signal prior to writing the composite informationsignal on the record carrier.
 16. Method for carrying out an encoding ofa digital information signal, such as a digital audio signal, in anapparatus as claimed in anyone of the claims 1 to
 15. 17. Methods asclaimed in claim 16, further comprising the step of writing thecomposite information signal on a record carrier.
 18. Record carriercomprising the composite information signal as generated by theapparatus as claimed in anyone of the claims 1 to 15, in a track on saidrecord carrier.
 19. Apparatus for decoding an encoded compositeinformation signal comprising encoded data of an n-channel digitalinformation signal, such as an n-channel digital audio signal, where nis an integer larger than 1, and side information having a relationshipwith said encoded digital information signal, the apparatus comprisinginput means for receiving a composite information signal, retrievalmeans for retrieving encoded data information and side information fromsaid composite information signal, decoding means for decoding theencoded data information so as to obtain said n channel signals inresponse to a set of probability values for each of said channelsignals, prediction filter means for carrying out a prediction filteringon each of said channel signals of the n-channel digital audio signal inresponse to n sets of prediction filter coefficients, one set for eachof said channel signals, so as to obtain a prediction filtered channelsignal from each of said channel signals, said sets of prediction filtercoefficients being derived from said side information, probability valuegenerator means for generating n sets of probability values, one foreach of the channel signals in response to a corresponding predictionfiltered channel signal and corresponding probability table, said nprobability tables, one for each of the channel signals, being derivedfrom said side information, the retrieval means further being adapted toretrieve first and second mapping information, a plurality of m sets ofprediction filter coefficients and a plurality of p probability tablesfrom said side information, reconverting means for reconverting saidfirst mapping information and said m sets of prediction filtercoefficients into n sets of prediction filter coefficients, one set foreach of said channel signals, where m is an integer for which holds1≦m≦n, and for reconverting said second mapping information and said pprobability tables into n probability tables, one set for each of saidchannel signals, where p is an integer for which holds 1≦p≦n, outputmeans for outputting said n channel signals.
 20. Apparatus for decodingan encoded composite information signal comprising encoded data of ann-channel digital information signal, such as an n-channel digital audiosignal, where n is an integer larger than 1, and side information havinga relationship with said encoded digital information signal, theapparatus comprising input means for receiving a composite informationsignal, retrieval means for retrieving encoded data information and sideinformation from said composite information signal, decoding means fordecoding the encoded data information into M signal portions in responseto corresponding sets of probability values, one for each of said Msignal portions, where$M = {\sum\limits_{i = 0}^{i = {n - 1}}{sp}_{i}}$

and sp_(i) is the number of segments in the time equivalent signal blockof the i-th channel signal, probability value generator means forgenerating M sets of probability values, one for each of the M signalportions in response to a corresponding probability table, said Mprobability tables, one for each of the signal portions, being derivedfrom said side information, the retrieval means further being adapted toretrieve first segment information and first mapping information and aplurality of m probability tables from said side information, where m isan integer for which holds 1≦m≦M, reconverting means for reconvertingsaid first mapping information and m probability tables into Mprobability tables, one for each of said signal portions, and forreconverting said first segment information into information about thelength and locations of the M segments in the n channel signals so as toobtain time equivalent signal blocks in said n channel signals, outputmeans for outputting the time equivalent signal blocks of said n channelsignals.
 21. Apparatus as claimed in claim 20, further comprisingprediction filter means for carrying out a prediction filtering on saidtime equivalent signal blocks of each of said channel signals of then-channel digital information signal by dividing the time equivalentsignal blocks into segments, and prediction filtering the signalportions of the channel signals in all P segments in said timeequivalent signal blocks and for all n channel signals, so as to obtaina prediction filtered signal portion for each of said P signal portionsin response to a set of prediction filter coefficients for each of saidsignal portions, where$P = {\sum\limits_{i = 0}^{i = {n - 1}}{sf}_{i}}$

and sf_(i) is the number of segments in the time equivalent signal blockof the i-th channel signal, the retrieval means further being adapted toretrieve second segment information, second mapping information and psets of prediction filter coefficients from said side information, wherep is an integer for which holds 1≦p≦P, the reconverting means furtherbeing adapted to reconvert the second segment information intoinformation about the length and locations of the P segments in the nchannel signals and for reconverting the p sets of prediction filtercoefficients into P sets of prediction filter coefficients, one for eachof said P signal portions, using said second mapping information. 22.Apparatus as claimed in claim 21, wherein the retrieval means areadapted to retrieve a first indicator word (w₁) from said sideinformation, said first indicator word, when being of a first value,indicating that the segmentation of the time equivalent signal blocksfor the probability tables is different from the segmentation of thetime equivalent signal blocks for the prediction filter coefficients,and when being of a second value, indicating that the segmentation ofthe time equivalent signal blocks for the probability tables is the sameas for the prediction filter coefficients, and for retrieving onesegment information only from the side information in the latter case,the reconverting means further being adapted to copy the said segmentinformation so as to obtain the first and second segment information, inthe latter case.
 23. Apparatus as claimed in claim 21, wherein theretrieval means is adapted to retrieve a second indicator word (w₂) fromsaid side information, said second indicator word, when being of a thirdvalue, indicating that the time equivalent signal blocks all have thesame segmentation for the prediction filter coefficients and, when beingof a fourth value, indicating that the time equivalent signal blockshave each a different segmentation for the prediction filtercoefficients, the retrieval means further being adapted to retrievesecond segment information for only one time equivalent signal blockfrom the side information in the case that the second indicator word hasthe third value and is adapted to retrieve second segment informationfor each of the time equivalent signal blocks in the case that thesecond indicator word has the fourth value, the reconverting means beingfurther adapted to copy the second segment information n−1 times so asto obtain the P segments of the time equivalent signal blocks of all nchannel signals, in the case that the second indicator word has thethird value.
 24. Apparatus as claimed in claim 21, wherein the retrievalmeans is adapted to retrieve a third indicator word (w₃) from said sideinformation, said third indicator word, when being of a fifth value,indicating that the time equivalent signal blocks all have the samesegmentation for the probability tables, and when being of a sixthvalue, indicating that the time equivalent signal blocks have each adifferent segmentation for the probability tables, that the retrievalmeans is further adapted to retrieve first segment information for onlyone time equivalent signal block in the case that the third indicatorword has the fifth value and is adapted to retrieve first segmentinformation for each of the time equivalent signal blocks in the casethat the third indicator word has the sixth value, and that thereconverting means is further adapted to copy the first segmentinformation for said one time equivalent signal block n-i times so as toobtain the M segments of the time equivalent signal blocks of all the nchannel signals, in the case that the third indicator word has the fifthvalue.
 25. Apparatus as claimed in claim 21, wherein the retrieval meansis adapted to retrieve a fourth indicator word (w₄) from said sideinformation, said fourth indicator word being of a seventh value,indicating that the mapping information for the probability tables isdifferent from the mapping information for the sets of prediction filtercoefficients and, when being of an eighth value, indicating that themapping information for the probability tables is the same as for theprediction filter coefficients, that the retrieval means is furtheradapted to retrieve only one mapping information from the sideinformation in the latter case, the reconverting means being furtheradapted to copy the mapping information retrieved in the case that thefourth indicator word has the eighth value.
 26. Apparatus as claimed inclaim 21, wherein the retrieval means is adapted to retrieve a fifthindicator word (w₅) from said side information, said fifth indicatorword, when being of a ninth value, indicating that the time equivalentsignal blocks all have the same mapping information for the predictionfilter coefficients and, when being of a tenth value, indicating thatthe time equivalent signal blocks have each a different mappinginformation for the prediction filter coefficients, that the retrievalmeans are further adapted to retrieve second mapping information foronly one time equivalent signal block in the case that the fifthindicator word has the ninth value and is adapted to retrieve secondmapping information for each of the time equivalent signal blocks in thecase that the fifth indicator word has the tenth value.
 27. Apparatus asclaimed in claim 20 or 21, the retrieval means being further adapted toconverting information to retrieve a number code for a time equivalentsignal block from said side information, said number code representingthe number of segments in said time equivalent signal block. 28.Apparatus as claimed in claim 27, wherein said number code satisfies thefollowing table: S code(S) 1 1 2 01 3 001 4 0001 s 0^((s−1))1

where S is the number of segments in a time equivalent signal block of achannel signal.
 29. Apparatus as claimed in claim 21, wherein theretrieval means are adapted to retrieve a plurality of sets ofprediction filter coefficients from said side information and toretrieve an array of bits from the second mapping information, theapparatus further comprising allocation means for allocating the firstset of prediction coefficients to the first of said P segments, (a) theallocation means further being adapted to allocate the first set ofprediction filter coefficients to the second segment in response to thefirst bit in the array of bits being of a first binary value and beingadapted to allocate the second set of prediction filter coefficients tothe second segment in response to the first bit being of the secondbinary value, (b1) if the first set of coefficients is also the set offilter coefficients for the second segment, then the allocation means isfurther adapted to allocate to allocate the first set of predictionfilter coefficients to the third segment in response to the second bitin the array of bits being of a first binary value and is adapted toallocate the second set of prediction filter coefficients to the thirdsegment in response to the second bit being of the second binary value,(b2) if the second set of coefficients is the set of filter coefficientsfor the second segment, then the allocation means is further adapted toallocate either the first or the second or the third set of predictionfilter coefficients to the third segment in response to the values ofthe next two bits of the array of bits, (c1) if the first set of filtercoefficients is the set of filter coefficients for the second and thirdsegment, then the allocation means is further adapted to allocate eitherfirst or the second set of filter coefficients to the fourth segment inresponse to the value of the third bit of said array of bits, (c2) ifthe first set of prediction filter coefficients is the set of filtercoefficients for the second segment and the second set of filtercoefficients is the set of filter coefficients for the third segment,then the allocation means is further adapted to allocate either thefirst, or the second or the third set of prediction filter coefficientsto the fourth segment in response to the values of the third and fourthbits in said array of bits, (c3) if the second set of prediction filtercoefficients is the set of filter coefficients for the second segment,and the first or the second set of filter coefficients is the set offilters for the third segment, then the allocation means are adapted toallocate either the first, or second or the third set of filtercoefficients to the fourth segment in response to the values of thefourth and fifth bit in the array of bits (c4) if the second set ofprediction filter coefficients is the set of filter coefficients for thesecond segment, and the third set of filter coefficients is the set offilters for the third segment, then the allocation means are adapted toallocate either the first, or the second, or the third or the fourth setof filter coefficients to the fourth segment in response to the fourthand fifth bit in the array of bits.
 30. Apparatus as claimed in claim20, wherein the retrieval means are adapted to retrieve a plurality ofprobability tables from said side information and to retrieve an arrayof bits from the first mapping information, the apparatus furthercomprising allocation means for allocating the first probability tableto the first of said M segments, (a) the allocation means further beingadapted to allocate the first probability table to the second segment inresponse to the first bit in the array of bits being of a first binaryvalue and being adapted to allocate the second probability table to thesecond segment in response to the first bit being of the second binaryvalue, (b1) if the first probability table is also the probability tablefor the second segment, then the allocation means is further adapted toallocate the first probability table to the third segment in response tothe second bit in the array of bits being of a first binary value and isadapted to allocate the second probability table to the third segment inresponse to the second bit being of the second binary value, (b2) if thesecond probability table is the probability table for the secondsegment, then the allocation means is further adapted to allocate eitherthe first or the second or the third probability table to the thirdsegment in response to the values of the next two bits of the array ofbits, (c1) if the first probability table is the probability table forthe second and third segment, then the allocation means is furtheradapted to allocate either first or the second probability table to thefourth segment in response to the value of the third bit of said arrayof bits, (c2) if the first probability table is the probability tablefor the second segment and the second probability table is theprobability table for the third segment, then the allocation means isfurther adapted to allocate either the first, or the second or the thirdprobability table to the fourth segment in response to the values of thethird and fourth bits in said array of bits, (c3) if the secondprobability table is the probability table for the second segment, andthe first or the second probability table is the probability table forthe third segment, then the allocation means are adapted to allocateeither the first, or second or the third probability table to the fourthsegment in response to the values of the fourth and fifth bit in thearray of bits (c4) if the second probability table is the probabilitytable for the second segment, and the third probability table is theprobability table for the third segment, then the allocation means areadapted to allocate either the first, or the second, or the third or thefourth probability table to the fourth segment in response to the fourthand fifth bit in the array of bits.
 31. Apparatus as claimed in anyoneof the claims 19 to 30, characterized in that said input means comprisesreading means for reading the composite information signal from a recordcarrier.
 32. Apparatus as claimed in claim 31, characterized in thatsaid input means further comprises channel decoding and/or errorcorrection means for carrying out a channel decoding step and/or anerror correction step on the composite information signal prior tosupplying the composite information signal to the retrieval means. 33.Apparatus as claimed in claim 1, the encoding means being adapted toencode time equivalent signal blocks of each of said channel signals ofthe n-channel information signal, so as to obtain encoded timeequivalent signal blocks for each of said signal blocks in response toprobability values for each of said signal blocks, the prediction filtermeans being adapted to carry out a prediction filtering on each of saidtime equivalent signal blocks in response to said n sets of predictionfilter coefficients, one for each time equivalent signal block, theprobability table determining means being adapted to generate said nprobability tables, one for each time equivalent signal block. 34.Apparatus as claimed in claim 33, wherein the conversion means isadapted to generate a first indicator word (w₄) of a first value,indicating that the mapping information for the probability tables isdifferent from the mapping information for the prediction filtercoefficients and of a second value indicating that the mappinginformation for the probability tables is the same as for the predictionfilter coefficients, and for supplying the first or the second mappinginformation only in the latter case, the combining means being adaptedto combine the first indicator word and the first mapping information orthe second mapping information only into said composite informationsignal, in the case that the first indicator word has the second value.35. Apparatus as claimed in claim 33, wherein the conversion means isadapted to generate a second indicator word (w₅) of a third valueindicating that the time equivalent signal blocks all have the samemapping information for the sets of prediction filter coefficients andis adapted to generate a second indicator word of a fourth valueindicating that the time equivalent signal blocks have each a differentmapping information for the sets of prediction filter coefficients, thatthe converting means is adapted to generate second mapping informationfor only one time equivalent signal block in the case that the secondindicator word has the third value and is adapted to generate secondmapping information for each of the time equivalent signal blocks in thecase that the second indicator word has the fourth value, and that thecombining means is further adapted to combine the second indicator wordinto said composite information signal.
 36. Apparatus as claimed inclaim 33, wherein the first set of prediction filter coefficients isallocated to the first of said n time equivalent signal blocks, saidsecond mapping information being devoid of mapping information formapping said first set of prediction filter coefficients to said firsttime equivalent signal block of said n time equivalent signal blocks,(a) the first bit in said second mapping information indicating whetherthe set of prediction filter coefficients for the second time equivalentsignal block is the first set of prediction filter coefficients or asecond set of prediction filter coefficients, (b1) if the first set ofprediction filter coefficients is also the set of filter coefficientsfor the second time equivalent signal block, then the second bit in saidsecond mapping information indicating whether the set of predictionfilter coefficients for the third time equivalent signal block is thefirst set of prediction filter coefficients or the second set ofprediction filter coefficients, (b2) if the second set of predictionfilter coefficients is the set of filter coefficients for the secondtime equivalent signal block, then the next two bits in the secondmapping information indicating whether the set of prediction filtercoefficients for the third time equivalent signal block is the first,the second or the third set of prediction filter coefficients, (c1) ifthe first set of prediction filter coefficients is the set of filtercoefficients for the second and third time equivalent signal block, thenthe third bit of said second mapping information indicates whether theset of prediction filter coefficients for the fourth time equivalentsignal block is the first or the second set of prediction filtercoefficients, (c2) if the first set of prediction filter coefficients isthe set of filter coefficients for the second time equivalent signalblock and the second set of prediction filter coefficients is the set offilter coefficients for the third time equivalent signal block, then thethird and fourth bit in said second mapping information indicatingwhether the set of prediction filter coefficients for the fourth timeequivalent signal block is the first, the second or the third set ofprediction filter coefficients, (c3) if the second set of predictionfilter coefficients is the set of filter coefficients for the secondtime equivalent signal block, and the first or the second set of filtercoefficients is the set of filter coefficients for the third timeequivalent signal block, then the fourth and fifth bit in the secondmapping information indicating whether the set of prediction filtercoefficients for the fourth time equivalent signal block is the first,second or the third set of prediction filter coefficients, (c4) if thesecond set of prediction filter coefficients is the set of filtercoefficients for the second time equivalent signal block, and the thirdset of filter coefficients is the set of prediction filter coefficientsfor the third time equivalent signal block, then the fourth and fifthbit in the second mapping information indicating whether the set ofprediction filter coefficients for the fourth time equivalent signalblock is the first, second, third or the fourth set of filtercoefficients.
 37. Apparatus as claimed in claim 33, wherein the firstprobability table is allocated to the first of said n time equivalentsignal blocks, said first mapping information being devoid of mappinginformation for mapping said first probability table to said first timeequivalent signal block of said n time equivalent signal blocks, (a) thefirst bit in said first mapping information indicating whether theprobability table for the second time equivalent signal block is thefirst probability table or a second probability table, (b1) if the firstprobability table is also the probability table for the second timeequivalent signal block, then the second bit in said first mappinginformation indicating whether the probability table for the third timeequivalent signal block is the first probability table or the secondprobability table, (b2) if the second probability table is theprobability table for the second time equivalent signal block, then thenext two bits in the first mapping information indicating whether theprobability table for the third time equivalent signal block is thefirst, the second or the third probability table, (c1) if the firstprobability table is the probability table for the second and third timeequivalent signal block, then the third bit of said first mappinginformation indicates whether the probability table for the fourth timeequivalent signal block is the first or the second probability table,(c2) if the first probability table is the probability table for thesecond time equivalent signal block and the second probability table isthe probability table for the third time equivalent signal block, thenthe third and fourth bit in said first mapping information indicatingwhether the probability table for the fourth time equivalent signalblock is the first, the second or the third probability table, (c3) ifthe second probability table is the probability table for the secondtime equivalent signal block, and the first or the second probabilitytable is the probability table for the third time equivalent signalblock, then the fourth and fifth bit in the first mapping informationindicating whether the probability table for the fourth time equivalentsignal block is the first, second or the third probability table, (c4)if the second probability table is the probability table for the secondtime equivalent signal block, and the third probability table is theprobability table for the third time equivalent signal block, then thefourth and fifth bit in the first mapping information indicating whetherthe probability table or the fourth time equivalent signal block is thefirst, second, third or the fourth probability table.
 38. Apparatus asclaimed in claim 19, wherein said decoding means are adapted to decodethe encoded data information into n time equivalent signal blocks, onefor each of the n channel signals, the retrieval means being adapted toretrieve a first indicator word (w₄) from said side information, saidfirst indicator word being of a first value, indicating that the mappinginformation for the probability tables is different from the mappinginformation for the sets of prediction filter coefficients and, whenbeing of a second value, indicating that the mapping information for theprobability tables is the same as for the prediction filtercoefficients, that the retrieval means is further adapted to retrieveonly one mapping information from the side information in the lattercase, the reconverting means being further adapted to copy the mappinginformation retrieved in the case that the first indicator word has theeighth value.
 39. Apparatus as claimed in claim 19, wherein saiddecoding means are adapted to decode the encoded data information into ntime equivalent signal blocks, one for each of the n channel signals,the retrieval means being adapted to retrieve a second indicator word(w₅) from said side information, said second indicator word, when beingof a third value, indicating that the time equivalent signal blocks allhave the same mapping information for the prediction filter coefficientsand, when being of a fourth value, indicating that the time equivalentsignal blocks have each a different mapping information for theprediction filter coefficients, that the retrieval means are furtheradapted to retrieve second mapping information for only one timeequivalent signal block in the case that the fifth indicator word hasthe third value and is adapted to retrieve second mapping informationfor each of the time equivalent signal blocks in the case that the fifthindicator word has the fourth value.
 40. Apparatus as claimed in claim19, wherein said decoding means are adapted to decode the encoded datainformation into n time equivalent signal blocks, one for each of the nchannel signals, the retrieval means being adapted to retrieve aplurality of sets of prediction filter coefficients from said sideinformation and to retrieve an array of bits from the second mappinginformation, the apparatus further comprising allocation means forallocating the first set of prediction coefficients to the first of saidn time equivalent signal blocks, (a) the allocation means further beingadapted to allocate the first set of prediction filter coefficients tothe second time equivalent signal block in response to the first bit inthe array of bits being of a first binary value and being adapted toallocate the second set of prediction filter coefficients to the secondtime equivalent signal block in response to the first bit being of thesecond binary value, (b1) if the first set of coefficients is also theset of filter coefficients for the second time equivalent signal block,then the allocation means is further adapted to allocate to allocate thefirst set of prediction filter coefficients to the third time equivalentsignal block in response to the second bit in the array of bits being ofa first binary value and is adapted to allocate the second set ofprediction filter coefficients to the third time equivalent signal blockin response to the second bit being of the second binary value, (b2) ifthe second set of coefficients is the set of filter coefficients for thesecond time equivalent signal block, then the allocation means isfurther adapted to allocate either the first or the second or the thirdset of prediction filter coefficients to the third time equivalentsignal block in response to the values of the next two bits of the arrayof bits, (c1) if the first set of filter coefficients is the set offilter coefficients for the second and third time equivalent signalblock, then the allocation means is further adapted to allocate eitherfirst or the second set of filter coefficients to the fourth timeequivalent signal block in response to the value of the third bit ofsaid array of bits, (c2) if the first set of prediction filtercoefficients is the set of filter coefficients for the second timeequivalent signal block and the second set of filter coefficients is theset of filter coefficients for the third time equivalent signal block,then the allocation means is further adapted to allocate either thefirst, or the second or the third set of prediction filter coefficientsto the fourth time equivalent signal block in response to the values ofthe third and fourth bits in said array of bits, (c3) if the second setof prediction filter coefficients is the set of filter coefficients forthe second time equivalent signal block, and the first or the second setof filter coefficients is the set of filters for the third timeequivalent signal block, then the allocation means are adapted toallocate either the first, or second or the third set of filtercoefficients to the fourth time equivalent signal block in response tothe values of the fourth and fifth bit in the array of bits (c4) if thesecond set of prediction filter coefficients is the set of filtercoefficients for the second time equivalent signal block, and the thirdset of filter coefficients is the set of filters for the third timeequivalent signal block, then the allocation means are adapted toallocate either the first, or the second, or the third or the fourth setof filter coefficients to the fourth time equivalent signal block inresponse to the fourth and fifth bit in the array of bits.
 41. Apparatusas claimed in claim 19, wherein said decoding means are adapted todecode the encoded data information into n time equivalent signalblocks, one for each of the n channel signals, the retrieval means beingadapted to retrieve a plurality of probability tables from said sideinformation and to retrieve an array of bits from the first mappinginformation, the apparatus further comprising allocation means forallocating the first probability table to the first of said n timeequivalent signal blocks, (a) the allocation means further being adaptedto allocate the first probability table to the second time equivalentsignal block in response to the first bit in the array of bits being ofa first binary value and being adapted to allocate the secondprobability table to the second time equivalent signal block in responseto the first bit being of the second binary value, (b1) if the firstprobability table is also the probability table for the second timeequivalent signal block, then the allocation means is further adapted toallocate the first probability table to the third time equivalent signalblock in response to the second bit in the array of bits being of afirst binary value and is adapted to allocate the second probabilitytable to the third time equivalent signal block in response to thesecond bit being of the second binary value, (b2) if the secondprobability table is the probability table for the second timeequivalent signal block, then the allocation means is further adapted toallocate either the first or the second or the third probability tableto the third time equivalent signal block in response to the values ofthe next two bits of the array of bits, (c1) if the first probabilitytable is the probability table for the second and third time equivalentsignal block, then the allocation means is further adapted to allocateeither first or the second probability table to the fourth timeequivalent signal block in response to the value of the third bit ofsaid array of bits, (c2) if the first probability table is theprobability table for the second time equivalent signal block and thesecond probability table is the probability table for the third timeequivalent signal block, then the allocation means is further adapted toallocate either the first, or the second or the third probability tableto the fourth time equivalent signal block in response to the values ofthe third and fourth bits in said array of bits, (c3) if the secondprobability table is the probability table for the second timeequivalent signal block, and the first or the second probability tableis the probability table for the third time equivalent signal block,then the allocation means are adapted to allocate either the first, orsecond or the third probability table to the fourth time equivalentsignal block in response to the values of the fourth and fifth bit inthe array of bits (c4) if the second probability table is theprobability table for the second time equivalent signal block, and thethird probability table is the probability table for the third timeequivalent signal block, then the allocation means are adapted toallocate either the first, or the second, or the third or the fourthprobability table to the fourth time equivalent signal block in responseto the fourth and fifth bit in the array of bits.